Accelerating multi-scale image fusion algorithms using CUDA

Seung H. Yoo, Jin Hyung Park, Chang-Sung Jeong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

Recently, fusion speed has emerged as an important factor in the image fusion and a substantial amount of memory and computing power are required for a high-speed fusion. This paper shows approaches to accelerate multi-scale image fusion speed on GPU (Graphics Processing Unit) using CUDA (Compute Unified Device Architecture). The GPU has evolved into a very powerful and flexible streaming processor, which provides a good computational power and memory bandwidth. We implement the multi-scale image fusion algorithms using CUDA software platform of the latest version of GPU and theirs fusion speeds are compared and evaluated with implementation in Core2 Quad processor with 2.4GHz. The GPU version achieved a speedup of 6x-8x over the CPU version.

Original languageEnglish
Title of host publicationSoCPaR 2009 - Soft Computing and Pattern Recognition
Pages278-282
Number of pages5
DOIs
Publication statusPublished - 2009 Dec 1
EventInternational Conference on Soft Computing and Pattern Recognition, SoCPaR 2009 - Malacca, Malaysia
Duration: 2009 Dec 42009 Dec 7

Other

OtherInternational Conference on Soft Computing and Pattern Recognition, SoCPaR 2009
CountryMalaysia
CityMalacca
Period09/12/409/12/7

Keywords

  • CUDA
  • GPU
  • Image fusion
  • Pyramid
  • Wavelet

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition
  • Software

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  • Cite this

    Yoo, S. H., Park, J. H., & Jeong, C-S. (2009). Accelerating multi-scale image fusion algorithms using CUDA. In SoCPaR 2009 - Soft Computing and Pattern Recognition (pp. 278-282). [5370356] https://doi.org/10.1109/SoCPaR.2009.63